Improving News Popularity Estimation via Weak Supervision and Meta-active Learning

Social news has fundamentally changed the mechanisms of public perception, education, and even dis-information. Apprising the popularity of social news articles can have significant impact through a diversity of information redistribution techniques. In this article, an improved prediction algorithm is proposed to predict the long-time popularity of social news articles without the need for ground-truth observations. The proposed framework applies a novel active learning selection policy to obtain the optimal volume of observations and achieve superior predictive performance. To assess the proposed framework, a large set of experiments are undertaken; these indicate that the new solution can improve prediction performance by 28% (precision) while reducing the volume of required ground truth by 32%

WeSAL: Applying Active Supervision to Find High-quality Labels at Industrial Scale

Obtaining hand-labeled training data is one of the most tedious and expensive parts of the machine learning pipeline. Previous approaches, such as active learning aim at optimizing user engagement to acquire accurate labels. Other methods utilize weak supervision to generate low-quality labels at scale. In this paper, we propose a new hybrid method named WeSAL that incorporates Weak Supervision sources with Active Learning to keep humans in the loop. The method aims to generate large-scale training labels while enhancing its quality by involving domain experience. To evaluate WeSAL, we compare it with two-state-of-the-art labeling techniques, Active Learning and Data Programming. The experiments use five publicly available datasets and a real-world dataset of 1.5M records provided by our industrial partner, IBM. The results indicate that WeSAL can generate large-scale, high-quality labels while reducing the labeling cost by up to 68% compared to active learning

Automated server-side model for recognition of security vulnerabilities in scripting languages

With the increase of global accessibility of web applications, maintaining a reasonable security level for both user data and server resources has become an extremely challenging issue. Therefore, static code analysis systems can help web developers to reduce time and cost. In this paper, a new static analysis model is proposed. This model is designed to discover the security problems in scripting languages. The proposed model is implemented in a prototype SCAT, which is a static code analysis Tool. SCAT applies the phases of the proposed model to catch security vulnerabilities in PHP 5.3. Empirical results attest that the proposed prototype is feasible and is able to contribute to the security of real-world web applications. SCAT managed to detect 94% of security vulnerabilities found in the testing benchmarks; this clearly indicates that the proposed model is able to provide an effective solution to complicated web systems by offering benefits of securing private data for users and maintaining web application stability for web applications providers

Assessment of serum interleukin 19 level in patients with warts

Background: Warts are viral cutaneous infections caused by human papilloma virus (HPV), presented by verrucous growth over the skin surface. The cell mediated immune response is considered to play a crucial role in HPV clearance. The viral load and number of lesions increase when there is an imbalance between the T-helper 1 and T-helper 2 immune responses. Interleukin (IL)-19 is a cytokine that belongs to interleukin 10 cytokines family and constitutes a sub-family with IL-20, IL-22 and IL-24. IL-19 is mainly produced by activated monocytes and to a lesser extent by B-cells, keratinocytes and fetal membranes. IL-19 was found to shift T-cell maturation away from the pro-inflammatory T-helper 1 cells toward the anti-inflammatory T-helper 2 cells. It induces IL-4 and IL-13 production in T cells and apoptosis in monocytes. Aim: This study aimed to measure serum level of IL-19 in patients with warts compared to healthy controls and to find out the correlation between this level and number, size and clinical types of warts. Methods: The study included 50 patients with warts and 50 control subjects. Serum concentration of IL-19 was measured by enzyme-linked immune sorbent assay. Results: Interleukin-19 serum level was significantly lower in patients with warts than in controls (P < 0.003). Moreover, there was a significant positive correlation between IL-19 serum level and the number of warts (P = 0.027). Conclusion: Serum level of IL-19 was significantly lower in patients with warts, and this low level might be crucial for an effective cell mediated immunological response to HPV

A comprehensive review of tools for exploratory analysis of tabular industrial datasets

Exploratory data analysis plays a major role in obtaining insights from data. Over the last two decades, researchers have proposed several visual data exploration tools that can assist with each step of the analysis process. Nevertheless, in recent years, data analysis requirements have changed significantly. With constantly increasing size and types of data to be analyzed, scalability and analysis duration are now among the primary concerns of researchers. Moreover, in order to minimize the analysis cost, businesses are in need of data analysis tools that can be used with limited analytical knowledge. To address these challenges, traditional data exploration tools have evolved within the last few years. In this paper, with an in-depth analysis of an industrial tabular dataset, we identify a set of additional exploratory requirements for large datasets. Later, we present a comprehensive survey of the recent advancements in the emerging field of exploratory data analysis. We investigate 50 academic and non-academic visual data exploration tools with respect to their utility in the six fundamental steps of the exploratory data analysis process. We also examine the extent to which these modern data exploration tools fulfill the additional requirements for analyzing large datasets. Finally, we identify and present a set of research opportunities in the field of visual exploratory data analysis. Keywords: Exploratory data analysis, Industrial tabular data, Interactive visualization, Systematic literature review, Research opportunitie

Goal-directed fluid therapy compared to liberal fluid therapy in patients subjected to colorectal surgery

ABSTRACTBackground The best technique to manage intraoperative fluids during colorectal surgery has never been universally agreed upon. Key organ function is hampered by excessive intraoperative fluid administration: It lengthens and raises the expense of hospitalization by increasing the risk of heart failure that goes along with it, causing gastrointestinal membrane edema, and impeding the recovery of gastrointestinal functions.Aim and objectives Thestudy’s objective was to evaluate the impacts of goal-directed fluid therapy (GDFT) and liberal fluid therapy (LFT) using cardiometry in candidates with colorectal abnormalities.Subjects and methods 100 patients were allocated into two equal groups in a random pattern for this prospective, randomized, controlled trial at the Mansoura oncology center; GDFT group) 50 patients): by using stroke volume optimization and the LFT group (50 patients): by using the traditional technique of fluid administration.Results Crystalloid and total fluids were significantly lower among GDFTgroup compared to LFT group. Both lactate and creatinine levels were slightly higher among the GDFT group than the LFT group but without a statistically significant difference. Postoperative complications were comparable between the studied groups.Conclusions However, GDFT needs lower total volume of fluids given to the patients it may not enhance patients’ postoperative outcomes after colorectal surgery compared to liberal fluid treatment. Moreover, both studied strategies did not affect organ perfusion, although serum lactate and serum creatinine were slightly higher with GDFT

Ultrasound-guided ilioinguinal/iliohypogastric nerve block compared to posterior quadratus lumborum block in patients undergoing inguinal hernia repair

ABSTRACTBackground “Ilioinguinal/iliohypogastric nerve block” (IINB) has been described as effective regional anesthetic method for providing analgesia after inguinal hernia operations. Other studies have also reported that the “posterior quadratus lumborum block” (PQLB) is an effective analgesic option for lower abdominal surgeries. Herein, we compared the previous two block techniques for postoperative pain management in adults undergoing unilateral inguinal hernia repair.Methods According to the block technique, 76 adult patients scheduled for inguinal hernioplasty under general anesthesia were randomly enrolled into two groups; the PQLB and IINB groups. The block was performed after skin closure and before patient extubation. Postoperative analgesic profiles were recorded in both groups.Results The PQLB had lower heart rate and mean arterial pressure readings during postoperative assessment compared to the other group. Pain scores showed a significant decline in association with the PQLB during the first postoperative day, which resulted in a significant decline in pethidine consumption (49.17 vs. 70 mg in the IINB group) and better patient satisfaction. The duration to the first analgesic request significantly increased in association with the PQLB (13.25 vs. 8.42 hours in the IINB group). The incidence of nausea and vomiting increased significantly in the IINB group secondary to increased pethidine requirements.Conclusion PQLB is superior to IINB in providing analgesia for patients undergoing inguinal hernia repair